Application of Perona Malik anisotropic diffusion on digital radiographic image

Perona Malik Anisotropic Diffusion (PMAD) is a very useful and efficient denoising technique if the parameters are properly selected. Overestimating the parameters may cause oversmoothed and underestimating it may leave unfiltered noise. This makes the selection of parameters a crucial process. In this paper the PMAD model is solved using a finite difference scheme The discretized model is evaluated using different diffusion coefficient of exponential and quadratic on defective radiographic images in terms of quality and efficiency. In the application of the PMAD model on image data, a set of defective radiographic images of welding is used as input data. Peak Signal to Noise Ratio (PSNR), Structural Similarity Measure (SSIM) and temporal time are used to evaluate the performance of the model. The implementation of the experiment has been carried out using MATLAB R2009a. In terms of quality, results show that the Quadratic Diffusion Coefficient Function (QDCF) provides better results compared with the Exponential Diffusion Coefficient Function (EDCF). In conclusion, the denoising effect using PMAD model based on finite difference scheme shows able to improve image quality by removing noise in the defective radiographic image